Fingerprint Liveness Detection Using Wavelet-Based Completed LBP Descriptor

  • Jayshree Kundargi
  • R. G. Karandikar
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 703)


Fingerprint-based authentication systems need to be secured against spoof attacks. In this paper, we propose completed local binary pattern (CLBP) texture descriptor with wavelet transform (WT) for fingerprint liveness detection. The fundamental basis of the proposed method is live, and spoof finger images differ in textural characteristics due to gray-level variations. These textural characteristics occur at various scales and orientations. CLBP has high discriminatory power as it takes into account local sign and magnitude difference with average gray level of an image. CLBP extended to 2-D Discrete WT (DWT), and 2-D Real Oriented Dual Tree WT (RODTWT) domain captures texture features at multiple scales and orientations. Each image was decomposed up to four levels, and CLBP features computed at each level are classified using linear and RBF kernel support vector machine (SVM) classifiers. Extensive comparisons are made to evaluate influence of wavelet decomposition level, wavelet type, number of wavelet orientations, and feature normalization method on fingerprint classification performance. CLBP in WT domain has proved to offer effective classification performance with simplicity of computation. While texture features at each scale contribute to performance, higher performance is achieved at lower decomposition levels of high resolution with db2 and db1 wavelets, RBF SVM and mean normalized features.


Fingerprint liveness detection Multiscale texture features Wavelet transform Completed local binary patterns Support vector machine 


  1. 1.
    T. Matsumoto, H. Matsumoto, K. Yamada, and S. Hoshino: Impact of Artificial Gummy Fingers on Fingerprint Systems. In: Proc. of SPIE, vol. 4677, pp. 275–289, (2002).Google Scholar
  2. 2.
    D. Baldissera, A. Franco, D. Maio, and D. Maltoni: Fake Fingerprint Detection by Odor Analysis. In: Proc. of International Conference on Biometric Authentication, (2006).Google Scholar
  3. 3.
    S.T.V. Parthasaradhi, R. Derakhshani, L.A. Hornak, and S. A C Schuckers: Time-series detection of perspiration as a liveness test in fingerprint devices. In: IEEE Transactions on Systems, Man, and Cybernetics, Part C, Applications and Reviews, vol. 35, no. 3, pp. 335–343, (2005).Google Scholar
  4. 4.
    Haralick R M, Shanmugam K, Dinstein I H.: Textural features for image classification. In: IEEE Transactions on Systems, Man and Cybernetics, vol. SMC-3,no. 6, pp. 610–621, (1973).Google Scholar
  5. 5.
    S. Nikam and S. Agarwal.: Texture and Wavelet-Based Spoof Fingerprint Detection for Fingerprint Biometric Systems. In: First International Conference on Emerging Trends in Engineering and Technology, pp. 675–680, (2008).Google Scholar
  6. 6.
    S. Nikam and S. Agarwal.: Fingerprint Liveness Detection using Curvelet Energy and Co-occurrence Signatures. In: IEEE Fifth International Conference on Computer Graphics, Imaging and Visualisation (CGIV), pp. 217–222, (2008).Google Scholar
  7. 7.
    S. Nikam and S. Agarwal.: Ridgelet-Based Fake Fingerprint Detection. In: Neurocomputing, 72, 2491–2506, (2009).Google Scholar
  8. 8.
    T. Ojala, M. Pietikainen, and T. Maenpaa.: Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. In: IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, no. 7, pp. 971–987, (2002).Google Scholar
  9. 9.
    X. Jia, X. Yang, Y. Zang, N. Zhang, R. Dai, J. Tian, and J. Zhao.: Multi-scale Block Local Ternary Patterns for Fingerprints Vitality Detection. In: International Conference on Biometrics (ICB), pages 1–6, (2013).Google Scholar
  10. 10.
    I. Selesnick, R. Baraniuk, and N. Kingsbury.: The dual-tree complex wavelet transform. In: IEEE Signal Process. Mag., vol. 22, no. 6, pp. 123–151, (2005).Google Scholar
  11. 11.
    Timo Ojala, Matti Pietikinen, and David Harwood.: A comparative study of texture measures with classification based on featured distributions. In: Pattern Recognition, vol. 29, no. 1, pp. 51–59, (1996).Google Scholar
  12. 12.
    Z. Guo, D. Zhang.: A completed modeling of local binary pattern operator for texture classification. In: IEEE Transaction on Image Processing, vol. 19, pp. 1657–1663, (2010).Google Scholar
  13. 13.
    L. Ghiani, D. Yambay, V. Mura, S. Tocco, G.L. Marcialis, F. Roli, and S. Schuckers.: LivDet 2013 Fingerprint liveness detection competition 2013. In: Proc. Int. Conf. Biometrics, pp. 1–6, (2013).Google Scholar
  14. 14.
    A. Abhyankar and S. Schuckers.: Fingerprint liveness detection using local ridge frequencies and multiresolution texture analysis techniques. In: Proc. IEEE International Conference on Image Processing, pp. 321–324, (2006).Google Scholar
  15. 15.
    S. Liao, X. Zhu, Z. Lei, L. Zhang, S. Z. Li.: Learning multi-scale block local binary patterns for face recognition. In: Proceedings of the ICB, (2007).Google Scholar
  16. 16.
    L. Ghiani, G. Marcialis, F. Roli.: Fingerprint Liveness Detection By Local Phase Quantization. In: International Conference on Pattern Recognition, pp. 537–540, (2012).Google Scholar
  17. 17.
    L. Ghiani, A. Hadid, G. Marcialis, F. Roli.: Fingerprint Liveness Detection Using Binarized Statistical Image Features. In: IEEE International Conference on Biometrics: Theory, Applications and Systems-BTAS, 2013, pp. 1–6, (2013).Google Scholar
  18. 18.
    D. Gragnaniello, G. Poggi, C. Sansone, and L. Verdoliva.: Local Contrast Phase Descriptor for Fingerprint Liveness Detection. In: Pattern Recognit., vol. 48, no. 4, pp. 1050–1058, (2015).Google Scholar
  19. 19.
    I. Daubechies.: Ten Lectures on Wavelets.: SIAM, (1992). Google Scholar
  20. 20.
    Boser, B.E., Guyon, I.M., and Vapnik, V.N.: A training algorithm for optimal margin classifiers. In: 5th Annual ACM Workshop on COLT, pp. 144–152, (1992).Google Scholar
  21. 21.
    Chih-Chung Chang and Chih-Jen Lin.: LIBSVM: a library for support vector machines. In: ACM Transactions on Intelligent Systems and Technology, 2:27:1—27:27, (2011).Google Scholar
  22. 22.
    Yambay, L. Ghiani, P. Denti, G. L. Marcialis, F. Roli, and S. Schuckers.: LivDet 2011 Fingerprint Liveness Detection Competition 2011. In: Proc. 5th IAPR/IEEE Int. Conf. Biometrics, pp. 208–215, (2012).Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.K. J. Somaiya College of EngineeringMumbaiIndia

Personalised recommendations